Bayesian Optimization based Nonlinear Adaptive PID Design for Robust Control of the Joints at Mobile Manipulators
Paper i proceeding, 2022

In this paper, we propose to use a nonlinear adaptive PID controller to regulate the joint variables of a mobile manipulator. The motion of the mobile base forces undue disturbances on the joint controllers of the manipulator. In designing a conventional PID controller, one should make a trade-off between the performance and agility of the closed-loop system and its stability margins. The proposed nonlinear adaptive PID controller provides a mechanism to relax the need for such a compromise by adapting the gains according to the magnitude of the error without expert tuning. Therefore, we can achieve agile performance for the system while seeing damped overshoot in the output and track the reference as close as possible, even in the presence of external disturbances and uncertainties in the modeling of the system. We have employed a Bayesian optimization approach to choose the parameters of a nonlinear adaptive PID controller to achieve the best performance in tracking the reference input and rejecting disturbances. The results demonstrate that a well-designed nonlinear adaptive PID controller can effectively regulate a mobile manipulator’s joint variables while carrying an unspecified heavy load and an abrupt base movement occurs.

Bayes methods

Tracking

Automation

Uncertainty

Computer aided software engineering

Manipulators

Stability analysis

Författare

Hadi Hajieghrary

Chalmers, Elektroteknik, System- och reglerteknik

Marc Peter Deisenroth

University College London (UCL)

Yasemin Bekiroglu

Chalmers, Elektroteknik, System- och reglerteknik

IEEE International Conference on Automation Science and Engineering

21618070 (ISSN) 21618089 (eISSN)

1009-1016

IEEE International Conference on Automation Science and Engineering (CASE)
Mexico City, Mexico,

Ämneskategorier

Robotteknik och automation

Reglerteknik

Signalbehandling

DOI

10.1109/CASE49997.2022.9926575

Mer information

Senast uppdaterat

2023-10-26